Title page for ETD etd-03082012-120707

Influence of Petroleum Deposit Geometry on Local Gradient of Electron Acceptors and Microbial Catabolic Potential

Degree

Master of Science

Department

Civil Engineering

Advisory Committee

Advisor Name

Title

Pruden-Bagchi, Amy Jill

Committee Chair

Widdowson, Mark A.

Committee Co-Chair

Novak, John T.

Committee Member

Keywords

Petroleum deposit

qPCR

DGGE

mcrA

dsrA

cat23

geometry

oil spill

gene biomarkers

coastal contamination

Deepwater Horizon

BP oil spill

Gulf of Mexico

Date of Defense

2012-02-27

Availability

unrestricted

Abstract

A field survey was conducted following the Deepwater Horizon blowout and it was noted that resulting coastal petroleum deposits possessed distinct geometries, ranging from small tar balls to expansive horizontal oil sheets. A laboratory study evaluated the effect of oil deposit geometry on localized gradients of electron acceptors and microbial community composition, factors that are critical to accurately estimating biodegradation rates. One-dimensional top-flow sand columns with 12-hour simulated tidal cycles compared two contrasting geometries (isolated tar “balls” versus horizontal “sheets”) relative to an oil-free control. Significant differences in the effluent dissolved oxygen and sulfate concentrations were noted among the columns, indicating presence of anaerobic zones in the oiled columns, particularly in the sheet condition. Furthermore, quantification of genetic markers of electron acceptor and catabolic conditions via quantitative polymerase chain reaction of dsrA (sulfate-reduction), mcrA (methanogenesis), and cat23 (oxygenation of aromatics) genes in column cores suggested more extensive anaerobic conditions induced by the sheet relative to the ball geometry. Denaturing gradient gel electrophoresis similarly revealed that distinct gradients of bacterial communities established in response to the different geometries. Thus, petroleum deposit geometry impacts local redox and microbial characteristics and may be a key factor for advancing attenuation models and prioritizing cleanup.